Albert M. Chan

Functional genomics reveal that the serine synthesis pathway is essential in breast cancer

Cancer cells adapt their metabolic processes to drive macromolecular biosynthesis for rapid cell growth and proliferation (1,2). RNAi-based loss of function screening has proven powerful for the identification of novel and interesting cancer targets, and recent studies have used this technology in vivo to identify novel tumor suppressor genes (3). Here, we developed a method for identifying novel cancer targets via negative selection RNAi screening in solid tumours. Using this method, we screened a set of metabolic genes associated with aggressive breast cancer and stemness to identify those required for in vivo tumourigenesis. Among the genes identified, phosphoglycerate dehydrogenase (PHGDH) is in a genomic region of recurrent copy number gain in breast cancer and PHGDH protein levels are elevated in 70% of ER-negative breast cancers. PHGDH catalyzes the first step in the serine biosynthesis pathway, and breast cancer cells with high PHGDH expression have elevations in serine synthesis flux. Suppression of PHGDH in cell lines with elevated PHGDH expression, but not those without, causes a strong decrease in cell proliferation and a reduction in serine synthesis. We find that PHGDH suppression does not affect intracellular serine levels, but causes a drop in the levels of alpha-ketoglutarate, another output of the pathway and a TCA cycle intermediate. In cells with high PHGDH expression, the serine synthesis pathway contributes approximately 50% of the total anaplerotic flux of glutamine into the TCA cycle. These results reveal that certain breast cancers are dependent upon increased serine pathway flux caused by PHGDH over-expression and demonstrate the utility of in vivo negative selection RNAi screens for finding potential anticancer targets.

A new reduced-complexity sphere decoder for multiple antenna systems

Sphere decoding for multiple antenna systems has been shown to achieve near-ML performance with low complexity. However, the achievement of such an excellent performance-complexity tradeoff is highly dependent on the initial choice of sphere radius. We present a new sphere decoding algorithm which is even less computationally complex than the original sphere decoder. Moreover, the complexity of the new sphere decoder is relatively insensitive to the initial choice of sphere radius. Thus, by making the choice of radius sufficiently large, the ML solution is guaranteed with low complexity, even for large constellations. In our simulations, we show that with 4 transmit and 4 receive antennas and 64-QAM, our new sphere decoding algorithm achieves the exact ML solution with approximately a factor of 3.5 reduction in complexity when compared to the original sphere decoder, and a factor of 10/sup 5/ reduction when compared to brute-force ML decoding.

Space-time bit-interleaved coded modulation for OFDM systems

Space-time coding techniques significantly improve transmission efficiency in radio channels by using multiple transmit and/or receive antennas and coordination of the signaling over these antennas. Bit-interleaved coded modulation gives good diversity gains with higher order modulation schemes using well-known binary convolutional codes on a single transmit and receive antenna link. By using orthogonal frequency division multiplexing (OFDM), wideband transmission can be achieved over frequency-selective fading radio channels without adaptive equalizers. In this correspondence, we combine these three ideas into a family of flexible space-time coding methods. The pairwise error probability is analyzed based on the correlated fading assumption. Near-optimum iterative decoders are evaluated by means of simulations for slowly varying wireless channels. Theoretical evaluation of the achievable degree of diversity is also presented. Significant performance gains over the wireless local area network (LAN) 802.11a standard system are reported.

On the asymptotic performance of the decorrelator

We derive the asymptotic signal-to-interference ratio (SIR) of the decorrelator in the large system limit, both for the case in which the number of users exceeds the spreading gain and for the case in which the number of users is less than the spreading gain. We show that, contrary to what is claimed by Tse and Hardy (see ibid., vol.45, p.641-57, Mar. 1999) and by Tse and Zeitouni (see ibid., vol.46, p.171-188, Jan. 2000) when the number of users exceeds the spreading gain and the decorrelator is defined in terms of the Moore-Penrose pseudoinverse, the SIR does not converge to zero.

Space-time bit-interleaved coded modulation for OFDM systems in wireless LAN applications

Space-time coding techniques are methods to improve transmission efficiency in radio channels by using multiple transmit and/or receive antennas. Bit-interleaved coded modulation gives good diversity gains with higher order modulation schemes using well known binary convolutional codes. By using orthogonal frequency division multiplexing (OFDM), wideband transmission can be achieved over frequency selective fading radio channels. In this paper, we combine these three ideas into a family of flexible space-time coding methods where modulation order and coding rates as well as the number of transmit and receive antennas can be changed without drastic redesign of the space-time codes. Near optimum iterative decoders are evaluated in terms of simulation for slowly varying wireless LAN type channels. Significant performance gains over the 802.11a standard system are reported.

Equalization of speech and audio signals using a nonlinear dynamical approach

We present the minimum phase space volume (MPSV) technique, a nonlinear dynamical technique for enhancing speech and audio signals corrupted by convolutional noise. The MPSV technique requires no assumptions or a priori information about the original signal, remains effective when the inverse filter order is overestimated, and significantly outperforms the LS method.

An optimal whitening approach to linear multiuser detection

We propose a new linear multiuser receiver for synchronous code-division multiple-access (CDMA) systems, referred to as the orthogonal multiuser (OMU) receiver. Unlike the linear minimum mean-squared error (MMSE) receiver, the OMU receiver depends only on the signature vectors and does not require knowledge of the received amplitudes or the channel signal-to-noise ratio (SNR). Several equivalent representations of the receiver are developed with different implications in terms of implementation. In the first, the receiver consists of a decorrelator demodulator followed by an optimal whitening transformation on a space formed by the signatures. In the second, the receiver consists of a bank of correlators with correlating vectors that are projections of a set of orthogonal vectors, and are closest in a least squares sense to the decorrelator vectors and also closest in a least squares sense to the signature vectors. In the third, the receiver consists of a single-user matched filter (MF) followed by an optimal whitening transformation on a space formed by the signatures. We derive exact and approximate expressions for the probability of bit error, as well as the asymptotic signal-to-interference+noise ratio (SINR) in the large system limit. The analysis suggests that over a wide range of channel parameters the OMU receiver can outperform both the decorrelator and the single-user MF and perform similarly to the linear MMSE receiver, despite not knowing the channel parameters.

Blind identification of an autoregressive system using a nonlinear dynamical approach

The problem of identifying an autoregressive (AR) system with arbitrary driven noise is considered here. Using an abstract dynamical system to represent both chaotic and stochastic processes in a unified framework, a dynamic-based complexity measure called phase space volume (PSV), which has its origins in chaos theory, can be applied to identify an AR model in chaotic as well as stochastic noise environments. It is shown that the PSV of the output signal of an inverse filter applied to identify an AR model is always larger than the PSV of the input signal of the AR model. Therefore, by minimizing the PSV of the inverse filter output, one can estimate the coefficients and the order of the AR system. A major advantage of this minimum-phase space volume (MPSV) identification technique is that it works like a universal estimator that does not require precise statistical information about the AR input signal. Because the theoretical PSV is so difficult to compute, two approximations of PSV are also considered: the e-PSV and nearest neighbor PSV. Both approximations are shown to approach the ideal PSV asymptotically. The identification performance based on these two approximations are evaluated using Monte Carlo simulations. Both approximations are found to generate relatively good results in identifying an AR system in various noise environments, including chaotic, non-Gaussian, and colored noise.

A New Class of Efficient Block-Iterative Interference Cancellation Techniques for Digital Communication Receivers

A new and efficient class of nonlinear receivers is introduced for digital communication systems. These “iterated-decision” receivers use optimized multipass algorithms to successively cancel interference from a block of received data and generate symbol decisions whose reliability increases monotonically with each iteration. Two variants of such receivers are discussed: the iterated-decision equalizer and the iterated-decision multiuser detector. Iterated-decision equalizers, designed to equalize intersymbol interference (ISI) channels, asymptotically achieve the performance of maximum-likelihood sequence detection (MLSD), but only have a computational complexity on the order of a linear equalizer (LE). Even more importantly, unlike the decision-feedback equalizer (DFE), iterated-decision equalizers can be readily used in conjunction with error-control coding. Similarly, iterated-decision multiuser detectors, designed to cancel multiple-access interference (MAI) in typical wireless environments, approach the performance of the optimum multiuser detector in uncoded systems with a computational complexity comparable to a decorrelating detector or a linear minimum mean-square error (MMSE) multiuser detector.

Approaching the matched-filter bound using iterated-decision equalization with frequency-interleaved encoding

We propose a new low-complexity strategy for approaching the matched filter bound on most practical ISI channels. At the transmitter, a form of channel-independent precoding is introduced to perform frequency-interleaving, which appropriately conditions the channel. At the receiver, a very low-complexity iterated-decision equalizer (Chan, A.M. and Wornell, G.W., IEEE Trans. Commun., vol.49, p.1966-76, 2001) is used. As an illustration, we use the system to attain the matched filter bound effectively on the 1+D channel without the use of error-control coding.